The problem of Causal Structure Discovery is defined by given inputs, outputs, auxiliary knowledge of components and possible internal connections. constraints programming is employed to discover admissible system mod...
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ISBN:
(数字)9783319604381
ISBN:
(纸本)9783319604381;9783319604374
The problem of Causal Structure Discovery is defined by given inputs, outputs, auxiliary knowledge of components and possible internal connections. constraints programming is employed to discover admissible system models. Existence of internal connections and predefined functionality of components is handled through reification.
Cloud computing is the widely spread paradigm of utility-computing that offers an "on-demand" internet-based access to configurable resources available within data centers. On one hand, public Cloud provider...
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ISBN:
(纸本)9781538621295
Cloud computing is the widely spread paradigm of utility-computing that offers an "on-demand" internet-based access to configurable resources available within data centers. On one hand, public Cloud providers are well suited for highly available access to IT resources (infrastructure, platform and software), for sporadic use, or for elastic demands. On the other hand, private clouds could sometimes be preferred for security or privacy reasons, or for cost reasons due to a high frequency usage of services. However, in many cases a choice between public or private clouds does not fulfill all requirements of companies, and hybrid cloud infrastructures should be preferred. A hybrid cloud solution could, for example, answer sudden workload increase in private clouds, security or fault tolerance requirements, or even latency issues thanks to data-locality. Solutions have already been proposed to address hybrid cloud infrastructures, however most of the time the placement of a distributed software on such infrastructure has to be indicated manually. For this reason, the automation of software deployment on hybrid clouds is still under research. In this paper we propose new specific placement constraints and objectives adapted to hybrid clouds infrastructures within our placement solution, namely OptiPlace, and we address this problem through constraint programming. Furthermore, we evaluate the expressivity and performance of the proposed solution on a real case study.
Effective general-purpose search strategies are an important component in constraint programming. We introduce a new idea, namely, using correlations between variables to guide search. Variable correlations are measur...
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ISBN:
(纸本)9781538638767
Effective general-purpose search strategies are an important component in constraint programming. We introduce a new idea, namely, using correlations between variables to guide search. Variable correlations are measured and maintained by using domain changes during constraint propagation. We propose two variable heuristics based on the correlation matrix, crbs-sum and crbs-max. We evaluate our correlation heuristics with well known heuristics, namely, domiwdeg, impact-based search and activity-based search. Experiments on a large set of benchmarks show that our correlation heuristics are competitive with the other heuristics, and can be the fastest on many series.
The use of restart techniques in complete Satisfiability (SAT) algorithms has made solving hard real world instances possible. Without restarts such algorithms could not solve those instances, in practice. State of th...
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The use of restart techniques in complete Satisfiability (SAT) algorithms has made solving hard real world instances possible. Without restarts such algorithms could not solve those instances, in practice. State of the art algorithms for SAT use restart techniques, conflict clause recording (nogoods), heuristics based on activity variable in conflict clauses, among others. Algorithms for SAT and constraint problems share many techniques; however, the use of restart techniques in constraint programming with finite domains (CP(FD)) is not widely used as it is in SAT. We believe that the use of restarts in CP(FD) algorithms could also be the key to efficiently solve hard combinatorial problems. In this PhD thesis we study restarts and associated techniques in CP(FD) solvers. In particular, we propose to including in a CP(FD) solver restarts, nogoods and heuristics based in nogoods as this should improve search algorithms, and, consequently, efficiently solve hard combinatorial problems. We thus intend to: a) implement restart techniques (successfully used in SAT) to solve constraint problems with finite domains; b) implement nogoods (learning) and heuristics based on nogoods, already in use in SAT and associated with restarts; and c) evaluate the use of restarts and the interplay with the other implemented techniques. We have conducted the study in the context of domain splitting backtrack search algorithms with restarts. We have defined domain splitting nogoods that are extracted from the last branch of the search algorithm before the restart. And, inspired by SAT solvers, we were able to use information within those nogoods to successfully help the variable selection heuristics. A frequent restart strategy is also necessary, since our approach learns from restarts.
Anti-unification refers to the process of generalizing two (or more) goals into a single, more general, goal that captures some of the structure that is common to all initial goals. In general one is typically interes...
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This study presents a constraint programming (CP) approach for modeling batch operations both in fab (incompatible job families) and backend (compatible job families) which involves the constraints of different job re...
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ISBN:
(纸本)9781509054497
This study presents a constraint programming (CP) approach for modeling batch operations both in fab (incompatible job families) and backend (compatible job families) which involves the constraints of different job release times, non-identical job sizes, and different batch size. We formulate this scheduling problem as CP and compare with a mixed integer programming (MIP) approach. The models are tested on a set of common problem instances from a paper in the literature. Computational results show that CP outperforms the MIP approach with respect to solution quality and run time.
This paper considers the integrated problem of quay crane assignment, quay crane scheduling, yard location assignment, and vehicle dispatching operations at a container terminal. The main objective is to minimize vess...
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ISBN:
(纸本)9783319930312;9783319930305
This paper considers the integrated problem of quay crane assignment, quay crane scheduling, yard location assignment, and vehicle dispatching operations at a container terminal. The main objective is to minimize vessel turnover times and maximize the terminal throughput, which are key economic drivers in terminal operations. Due to their computational complexities, these problems are not optimized jointly in existing work. This paper revisits this limitation and proposes Mixed Integer programming (MIP) and constraint programming (CP) models for the integrated problem, under some realistic assumptions. Experimental results show that the MIP formulation can only solve small instances, while the CP model finds optimal solutions in reasonable times for realistic instances derived from actual container terminal operations.
The objective of airline manpower planning is to have the right number of pilots with the right qualifications at the right time. To accomplish this, one has to solve the subproblem of assigning pilots to promotion co...
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The objective of airline manpower planning is to have the right number of pilots with the right qualifications at the right time. To accomplish this, one has to solve the subproblem of assigning pilots to promotion courses such that pilots' seniority ranks and preferences are taken into account: no senior pilot should be able to find a junior pilot with a promotion that the senior pilot would have preferred. We call this subproblem the airline promotion assignment problem (APA). The objective of this thesis is to develop an efficient model for APA. We show how APA can be modelled as a stable matching problem, and more specifically how it can be formulated as an instance of the hospitals/residents prob- lem with ties and forbidden pairs. A constraint satisfaction problem model for APA is presented, which we have implemented in a constraint programming system. We also present a model for an extension to APA, which we call the airline promo- tion assignment problem with detailed preferences (APA-D), and which involves additional rules used within a specific airline. We show results from running our constraint programming implementation on different types of test data derived from real airline data. The thesis is concluded with a discussion of our work and some remarks on how the problem could be modelled and solved differently.
We present a method for solving programming by Example (PBE) problems that tightly integrates a neural network with a constraint logic programming system called miniKanren. Internally, miniKanren searches for a progra...
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The Spatial Packaging Problem (SPP) aims to solve a mixture of the 3D Packing Problem (3DPP) and the 3D Pipe-Routing Problem. The main feature that distinguishes the SPP from the traditional 3DPP is the interconnectio...
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ISBN:
(纸本)9783319339542;9783319339535
The Spatial Packaging Problem (SPP) aims to solve a mixture of the 3D Packing Problem (3DPP) and the 3D Pipe-Routing Problem. The main feature that distinguishes the SPP from the traditional 3DPP is the interconnections that exist between its components. The SPP is more challenging because the shape and dimensions of the interconnections are unknown, and must be determined as part of the solution. In this paper, we propose a relaxation, a constraint programming model and a search heuristic to solve the SPP. We relax the SPP by using taxicab geometry and model it as a constraint satisfaction problem, then solve it by using a search heuristic based on interconnection volumes. The proposed approach has been evaluated on a challenging benchmark that reflects a range of aerospace and commercial applications varying in number of components and interconnections. The preliminary results show the effectiveness and efficiency of the proposed approach.
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